How would you define and calculate Weekly Active Users (WAU)?

WHAT THIS TESTS: This question assesses your product thinking and data literacy. The interviewer wants to see if you can move from a vague business concept ('active users') to a concrete, defensible technical definition. They are testing your ability to define what 'value' looks like for a user, identify key actions, and foresee the technical challenges and biases in measurement. For a senior role, simply saying 'count distinct users' is not enough; you must show you understand the nuances.

A GOOD ANSWER COVERS: A strong answer has three parts. First, define the terms. A 'user' is a unique human, not a bot or test account. 'Active' should be tied to a core value-providing action, not a passive one. For Slack, this might be sending a message, adding a reaction, or joining a huddle, but NOT just opening the app. Second, explain the technical calculation. This usually involves a SQL query on an event log table, like SELECT COUNT(DISTINCT user_id) FROM events WHERE event_time >= NOW() - INTERVAL '7 days' AND event_name IN ('message_sent', 'reaction_added') AND is_bot = false;. Mention using a rolling 7-day window. Third, proactively discuss pitfalls. This includes filtering out bots (e.g., via a user_type flag or naming convention), internal employees (based on email domain), and automated background sync events that don't represent user intent.

COMMON WRONG ANSWERS: A major red flag is defining 'active' as simply 'opening the app' or 'logging in.' This is a vanity metric. It overcounts users who open the app from a notification but don't engage, and it doesn't correlate with actual product value. Another mistake is forgetting to mention COUNT(DISTINCT user_id), which would lead to counting events instead of users. Failing to mention filtering bots or internal users shows a lack of experience with real-world data, which is never perfectly clean.

LIKELY FOLLOW-UPS: How would you calculate WAU/MAU stickiness? How would this definition change for a different product, like a photo-sharing app or an e-commerce site? How would you handle a user who is active in multiple Slack workspaces? (This tests your understanding of user identity models). How would you set up A/B tests to validate that your chosen 'active' events actually correlate with retention?

ONE CONCRETE EXAMPLE: For Slack, a good 'active' event is message_sent. A bad one is app_opened. A message_sent event shows a user is contributing to a conversation, the core loop of the product. An app_opened event could just be an accidental tap. If WAU based on app_opened is 1M, but WAU based on message_sent is only 300k, it tells you that 70% of your weekly 'users' aren't actually getting the core value, which is a critical insight. The definition directly impacts business strategy.